How accurate are the results when I use optical modeling?
This is hard to tell, and it depends on many details. So there is no general answer to this question.
A good optical model should use the lowest possible number of parameters. If you have too many parameters in the model they may be correlated in a way that raising one parameter value and decreasing another leads to the same optical spectra. In this case the parameter values are more or less arbitrary, and the accuracy is very low.
The result of a parameter fit depends very much on the information contained in the measured data. If you want to determine a layer thickness, for example, you must have measured contributions of radiation which has seen the bottom of the layer, i.e. which has travelled through the layer at least once. If that is not the case in the spectral range that is accessible to you, you will never be able to get the thickness of the layer.
Can I get anything real out of a model?
Yes, of course. If your model is good, and your spectra do contain enough information, the parameter values reflect the real values as good as they can.
Please have in mind that in many cases talking about ‘real values’ is using a model in itself. If you ask for the real value of a layer thickness, for example, your question implies that there is something like a layer with a top and a bottom end. You ignore the atomic structure and surface roughness effects, or, if not, you apply (at least in your mind) a certain roughness averaging procedure.
The computation of depth dependent, local absorption in layer stacks is much faster now.
This improvement speeds up objects of type “Local absorption” in the list of distributions, but also objects of type “Layer absorption” and “Charge carrier generation” in the list of spectra.
In CODE the computation of the integral quantity “Photo current” benefits from the enhancement.
Certain parameter combinations of Gervais oscillators may lead to unphysical optical constants (i.e. negative imaginary part of the dielectric function). Physical meaningful solutions satisfy a sum rule for the damping constants which may be used to steer the fit into the direction of ‘good’ solutions.
The “check sum” (sum of the difference of LO damping and TO damping for all oscillators) can now be obtained as optical function. Use the optical function “my_material (Gervais_condition)” to retrieve the current value of the check sum.
In order to make use of this number in a fit you can proceed like this(this hint will work in CODE only): Generate an integral quantity of type ‘function of int. quant.’ and call it ‘Gervais check sum’. As formula to compute the value use the term “of(1)” (here it is assumed that the check sum is the first optical function). So the integral quantity is the check sum itself.
Now define a penalty shape function for this integral quantity. It should be 0 if the check sum is positive, and get large for large negative values of the check sum. An expression like “abs(y)*step(-y)y)” will do the job (in penalty shape functions for integral quantities the symbol “y” refers to the current value of the integral quantity). This way large negative values of the check sum are severely punished whereas positive values do not contribute to the fit deviation at all.
Finally activate the option “Combine fit deviations of integral quantities and spectra” in the fit options dialog (File/Options/Fit). This lets CODE simultaneously minimize the difference of measured and simulated spectra and the fit deviation of the integral quantities (which is in this case the penalty for an unphysical check sum). Eventually you have to experiment a little bit with the weight of the ‘Gervais check sum’ in the list of integral quantities in order to get a good fit.
Using several Gervais oscillators at the same time eventually caused numerical problems. This has been fixed today – you can now really use all 10 oscillators which are offered by the “Gervais dialog”.